Experimental Investigation on the Performance of Different Cutting Fluids on Cutting Force During Turning of Duplex Stainless Steel-2205 under MQL Technique

Author:

S.T. Prashantha Kumar,H.P. Thirtha Prasada,M. Nagamadhu,Pattar Niranjan,Kivade S.B.,Sachinkumar ,K.R. Ravichandra,S. Hanumanthlal

Abstract

Duplex stainless steel (DSS)-2205 comes under hard-to-machine material owing to its inherent properties but more applications in severe working conditions. Hence, investigating the effect of cutting fluids and machining parameters is essential. In the present work, an attempt has been made with Minimum Quantity Lubrication (MQL) the investigate the performance of Deionized (DI) water, neat cut oil, and emulsified fluid on Cutting Force (CF) during turning of Duplex Stainless Steel (DSS-2205). The experiments were conducted based on face central composite design (CCF) in response surface methodology, varying speed, feed, and depth of cut in three levels. The Analysis of Variance (ANOVA) is to identify significant factors that influence the response. The results revealed that using emulsified fluid's cutting force gives better results than the DI water and neat cut oil. Feed rate is the most significant factor for emulsified fluid contribution was 53.61% for neat cut oil 48.89% and DI water 26.11%. It also reveals that the contribution of the depth of cut is slightly lesser than the feed rate. However, the contributions of cutting speed in all three Deionized (DI) water, neat cut oil, and emulsified fluid working fluids are negligible.

Publisher

International Information and Engineering Technology Association

Subject

Applied Mathematics,Engineering (miscellaneous),Modeling and Simulation

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Predictive Modelling of Cutting Force in the Machining of Duplex Stainless Steels Using Artificial Neural Network;Proceedings of International Conference on Intelligent Manufacturing and Automation;2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3